Role of [18F]fluorodeoxyglucose positron emission tomography-computed tomography metabolic radiomics in predicting response to chemotherapy in patients with non-small cell lung cancer

RATIONALE: Accurate early prediction of chemotherapy response in non-small cell lung cancer (NSCLC) remains a clinical challenge. This study aimed to evaluate the utility of PET-based radiomic features extracted from [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) PET/computed tomography (CT) scans in predicting treatment response to platinum based chemotherapy in NSCLC patients. METHODS: An ambispective observational study was conducted on 70 histopathologically confirmed NSCLC patients who underwent [ 18 F]FDG PET/CT imaging before and after chemotherapy at a tertiary cancer center. Radiomic features were extracted from the primary lesion using commercially available texture analysis software, applying a fixed standardized uptake value (SUV) threshold-based volume of interest segmentation. Conventional metabolic parameters [SUVmax, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis (TLG)] and 46 radiomic features (GLRLM, NGLDM, GLCM, shape features) were analyzed. Treatment response was assessed using PERCIST criteria and patients were categorized as responders or non-responders. Statistical analysis included Mann-Whitney U test and receiver operating characteristic analysis to determine discriminatory ability of parameters. RESULTS: Among the radiomic and metabolic parameters evaluated, only a few showed statistically significant differences between responders and non-responders. GLRLM GLNU, GLCM correlation, NGLDM contrast, and shape surface demonstrated fair predictive performance with area under the curve (AUC) values >0.7. Conventional parameters such as SUVmax and TLG did not show statistically significant differences. The optimal cutoff values, sensitivity, specificity, AUCs, and P values of significant features were also obtained. CONCLUSION: Select radiomic features derived from [ 18 F]FDG PET/CT scans, particularly GLNU, GLCM correlation, and NGLDM contrast, hold promise in predicting response to platinum-based chemotherapy in NSCLC. These findings suggest the potential utility of radiomics in enhancing personalized treatment strategies, although further validation is warranted.